CN102853793B - Coordinate transformation data processing method and coordinate transformation data processing device - Google Patents

Abstract

The invention discloses a coordinate transformation data processing method and a coordinate transformation data processing device. An original rectangular coordinate system and a target rectangular coordinate system of a coordinate system A for measuring data of a target point are provided with at least three common points which do not stay on the same straight line. The coordinate transformation data processing method comprises following steps of receiving coordinate data in two coordinate systems of the common points, adopting the coordinate data of partial or all common points to construct a regression function by utilizing a least square method, and obtaining an iteration matrix making the regression function obtain a minimal value through iteration; adopting three common points which do not stay on the same straight line to calculate an initial value of coordinate transformation parameters between two coordinate systems; performing the iteration by adopting the calculated initial value of the coordinate transformation parameter as the initial value of the iteration matrix, and obtaining a real coordinate transformation parameter when the required precision is met through the iteration; and obtaining a coordinate of all points of the original rectangular coordinate system in the target rectangular coordinate system by utilizing the obtained real coordinate transformation parameters. Due to the adoption of the method and the device, precision in processing the data is realized, and the efficiency is high.

Description

Coordinate transform data processing method and device

Technical field

The present invention relates to the data processing field of measurement data, particularly relate to the unified coordinate transform data processing method of a kind of coordinate system of the measurement data for impact points all in fields of measurement and a kind of coordinate transform data treating apparatus.

Background technology

Along with the progress of science and technology, directly accurately the three-dimensional coordinate of measuring target point becomes possibility within the specific limits, and wherein the representational instrument of most is exactly laser tracker.

For laser tracker, full institute cannot be surveyed a little at erect-position when doing large-range measuring, so just needing to move instrument, multiple different erect-position complete measurement a little.Instrument uses local coordinate when each erect-position is measured, final need to obtain be the coordinate a little in same coordinate system, this just needs to adopt certain coordinate transform data processing method to process the measurement data in each coordinate system.

The position measurement of partial target point can only be completed at each station of instrument, to set up in this station survey the mutual alignment relation of impact point under instrument coordinates system, and each station the position surveyed between impact point be do not unify position relationship.Need to know the mutual alignment relation of all impact points under a unified coordinate system when initial data carries out treatment and analysis to measuring.Namely equitant region between each survey station, also have the impact point of duplicate measurements, is the common point between two coordinate systems.Therefore, just to need the data unification in different coordinates when processing measurement data, in unified coordinate system, namely to face the coordinate system reunification of measurement data.

Same needs also occurs in multiple instrument combined measurement.In order to reach high-precision measurement in Practical Project, often needing multiple instrument combined measurement, giving full play to the measurement advantage of various instrument.Such as GPS is applicable to doing large-scale measurement, and total powerstation is applicable to the measurement of distance in work, and laser tracker is applicable to doing in-plant measurement.They all have the measurement advantage that other instruments cannot replace in respective measurement category.But instrument not of the same race has respective coordinate system, survey data and cannot unify, namely face the problem that the coordinate system of measurement data is unified.

In addition, time in engineering or experiment for determining the position of impact point, the problem of the coordinate unification of measurement data is faced too.In engineering or experiment, often need a certain equipment to adjust to pre-designed position, whether foundation correctly in place is exactly whether the impact point that on this equipment, we are concerned about reaches precalculated position to equipment.The impact point of actual conditions often on this equipment cannot monitor after device assembles is good at all, with regard to needing the position that can monitor in device external in advance, some reference points are laid for this situation, first set up these reference points and the position relationship of impact point in device coordinate system, then measure these reference points when the equipment of adjustment.Now these reference points are exactly the common point between device coordinate system and instrument coordinates system.A kind of very common situation is also had to be need adjustment equipment to make the reference point on equipment arrive position pre-designed in specified coordinate system.The monitoring of equipment reference point locations realizes by instrument, and the reference point on instrument monitoring equipment is carried out under instrument coordinates system, now just needs instrument coordinates system to be transformed into this coordinate system of specifying.We can lay some control points in advance in this specified coordinate system, apply this algorithm and just can be transformed into this coordinate system of specifying, then just can realize the object of monitoring equipment reference point in specified coordinate system behind these control points of apparatus measures.

Summary of the invention

For problems of the prior art, object of the present invention, for providing a kind of data accurately and the unified coordinate data processing method of the coordinate system of the high impact point measurement data for fields of measurement of efficiency, can not carry out the unified technical problem of the coordinate system of impact point measurement data quickly and accurately with the coordinate data processing method solving prior art.

Another object of the present invention is for providing a kind of data accurate and the coordinate data treating apparatus that efficiency is high.

For achieving the above object, technical scheme of the present invention is as follows:

A kind of coordinate transform data processing method, for by the coordinate data conversion process in former rectangular coordinate system being the data in target rectangular coordinate system, described former rectangular coordinate system and described target rectangular coordinate system have the common point not on same straight line of more than at least three, described coordinate transform data processing method comprises: step S1: the coordinate data in described former rectangular coordinate system and these two coordinate systems of described target rectangular coordinate system receiving described common point, regression function is constructed with the described coordinate data least square method of part or all of described common point, and draw and make described regression function obtain the Iterative Matrix of minimum of a value solution by iteration, step S2: calculate the coordinate conversion parameter initial value between described former rectangular coordinate system and described target rectangular coordinate system with three common points not on same straight line, step S3: the described coordinate conversion parameter initial value calculated using described step S1 carries out iteration as the initial value of described Iterative Matrix, iteration is to obtaining actual coordinate conversion parameter when meeting required precision, step S4: the actual coordinate conversion parameter obtained with step S3 obtain described former rectangular coordinate system coordinate a little in described target rectangular coordinate system.

A kind of coordinate transform data treating apparatus, for by the coordinate data conversion process in former rectangular coordinate system being the data in target rectangular coordinate system, described former rectangular coordinate system and described target rectangular coordinate system have the common point not on same straight line of more than at least three, described coordinate transform data treating apparatus comprises: constructing module, in order to receive the coordinate data in former rectangular coordinate system and these two coordinate systems of target rectangular coordinate system of common point, regression function is constructed with the described coordinate data least square method of part or all of described common point, and draw and make regression function obtain the Iterative Matrix of minimum of a value solution by iteration, Initial Value module: for calculating the coordinate conversion parameter initial value between former rectangular coordinate system and target rectangular coordinate system with the common point of three not on same straight line, iteration module: the initial value of the described Iterative Matrix that the described coordinate conversion parameter initial value calculated using described Initial Value module obtains as described constructing module carries out iteration, iteration is to obtaining actual coordinate conversion parameter when meeting required precision, conversion module: the actual coordinate conversion parameter obtained by described iteration module obtain former rectangular coordinate system coordinate a little in target rectangular coordinate system.

Beneficial effect of the present invention is, coordinate transform data processing method of the present invention and device, the initial value of Iterative Matrix is calculated by not on same straight line three common points chosen in impact point, also be the initial value of six parameters of transformation matrix of coordinates, iteration function is made to obtain minimum of a value in global scope, to reach the object of data fitting, the present invention has high accuracy and high efficiency feature in coordinate transform data process.A large amount of measured data and Lay Ka, FARO tracker Survey Software is utilized to compare the accuracy and high efficiency that all demonstrate coordinate transform data processing method of the present invention.

Accompanying drawing explanation

Fig. 1 is the flow chart of initial value obtaining step in the coordinate transform data processing method of the embodiment of the present invention.

Fig. 2 is the modular structure schematic diagram of the coordinate transform data treating apparatus of the embodiment of the present invention.

Detailed description of the invention

The exemplary embodiments embodying feature & benefits of the present invention will describe in detail in the following description.Be understood that the present invention can have various changes in different embodiments, it neither departs from the scope of the present invention, and explanation wherein and accompanying drawing are the use when explain in itself, and is not used to limit the present invention.

Below to process the measurement data of the multiple different erect-position of measuring instrument, specifically introduce coordinate transform data processing method and the device of the preferred embodiment of the present invention, measuring instrument is such as laser tracker.

The coordinate transform data processing method of the embodiment of the present invention, it mainly comprises following three steps:

Step S1: the coordinate data in described former rectangular coordinate system and these two coordinate systems of described target rectangular coordinate system receiving described common point, construct regression function with the described coordinate data least square method of part or all of described common point, and draw and make described regression function obtain the Iterative Matrix of minimum of a value solution by iteration;

Step S2: calculate the coordinate conversion parameter initial value between described former rectangular coordinate system and described target rectangular coordinate system with three common points not on same straight line;

Step S3: the described coordinate conversion parameter initial value calculated using described step S1 carries out iteration as the initial value of described Iterative Matrix, iteration is to obtaining actual coordinate conversion parameter when meeting required precision;

Step S4: the actual coordinate conversion parameter obtained with step S3 obtain described former rectangular coordinate system coordinate a little in described target rectangular coordinate system.

Coordinate data to be processed be measuring instrument gather from multiple erect-position measurement data time, the described measurement data of each described erect-position is based on a rectangular coordinate system of respective erect-position, the rectangular co-ordinate of one of them erect-position is selected to be target rectangular coordinate system, by the described measurement data of all the other erect-positions successively through above-mentioned steps S1, step S2, step S3 and step S4, can draw each erect-position coordinate a little in described target rectangular coordinate system, then gather and obtain each erect-position coordinate a little in target rectangular coordinate system.

That is, the measurement data of the multiple different erect-position of measuring instrument to be dealt with, select the rectangular co-ordinate of one of them erect-position to be target-based coordinate system, the measurement data of other erect-positions is all converted to the coordinate in chosen target-based coordinate system, to complete Coordinate Conversion data processing.

For the coordinate transform of the measurement data of each erect-position, be configured to obtain by the regression function of each former coordinate system to same target-based coordinate system coordinate conversion parameter with the part or all of common point of this erect-position with the erect-position being chosen to be target rectangular coordinate system, building method is as follows:

According to least square ratio juris, according to known rectangular coordinate system coordinate transform formula, namely coordinate system rotate, translation formula, above-mentioned matching needs to obtain six parameters of coordinate transform: namely around the anglec of rotation jx of X, Y, Z axis, jy, jz and translation distance kx, ky, kz along X, Y, Z axis.

For example bright how solved function is obtained below.

Be provided with one group of spatial point, their coordinates in two rectangular coordinate system in space are respectively:

In first (target) rectangular coordinate system:

A1 (a1x, a1y, a1z), a2 (a2x, a2y, a2z) ..., an (anx, any, anz); A1, a2, an are the mark of spatial point, and aix, aiy, aiz are respectively the x, y, z coordinate (i=1 of an ai ... n).

In second (former) rectangular coordinate system:

B1 (b1x, b1y, b1z), b2 (b2x, b2y, b2z) ..., bn (bnx, bny, bnz); Equally, b1, b2, bn are the mark of spatial point, and bix, biy, biz are respectively the x, y, z coordinate (i=1 of a b1 ... n).

Now by bi to ai(i=1 ... n) matching.

It is as follows that coordinate system rotates translation formula:

$M=\left[\begin{array}{cccc}\cos \left(\mathrm{jz}\right)*\cos \left(\mathrm{jy}\right)& \cos \left(\mathrm{jz}\right)*\sin \left(\mathrm{jy}\right)*\sin \left(\mathrm{jx}\right)-\sin \left(\mathrm{jz}\right)*\cos \left(\mathrm{jx}\right)& \cos \left(\mathrm{jz}\right)*\sin \left(\mathrm{jy}\right)*\cos \left(\mathrm{jx}\right)+\sin \left(\mathrm{jz}\right)*\sin \left(\mathrm{jx}\right)& \mathrm{kx}\\ \sin \left(\mathrm{jz}\right)*\cos \left(\mathrm{jy}\right)& \sin \left(\mathrm{jz}\right)*\sin \left(\mathrm{jy}\right)*\sin \left(\mathrm{jx}\right)+\cos \left(\mathrm{jz}\right)*\cos \left(\mathrm{jz}\right)& \sin \left(\mathrm{jz}\right)*\sin \left(\mathrm{jy}\right)*\cos \left(\mathrm{jx}\right)-\cos \left(\mathrm{jz}\right)*\sin \left(\mathrm{jx}\right)& \mathrm{ky}\\ -\sin \left(\mathrm{jy}\right)& \cos \left(\mathrm{jy}\right)*\sin \left(\mathrm{jx}\right)& \cos \left(\mathrm{jy}\right)*\cos \left(\mathrm{jx}\right)& \mathrm{kz}\end{array}\right]---\left(1\right)$

Wherein jx, jy, jz are the corner around X, Y, Z reference axis respectively, and kx, ky, kz are that coordinate origin is along X, Y, Z translation of axes amount.

For a bi, its coordinate value after coordinate transform meets following formula:

${\mathrm{bi}}^{\′}\left[\begin{array}{c}{\mathrm{bi}}^{\′}x\\ {\mathrm{bi}}^{\′y}\\ {\mathrm{bi}}^{\′}z\end{array}\right]=M*\left[\begin{array}{c}\mathrm{bix}\\ \mathrm{biy}\\ \mathrm{biz}\\ 1\end{array}\right]=$

$\left[\begin{array}{c}\cos \left(\mathrm{jz}\right)*\cos \left(\mathrm{jy}\right)*\mathrm{bix}+(\cos \left(\mathrm{jz}\right)*\sin \left(\mathrm{jy}\right)*\sin \left(\mathrm{jx}\right)-\sin \left(\mathrm{jz}\right)*\cos \left(\mathrm{jx}\right))*\mathrm{biy}+(\cos \left(\mathrm{jz}\right)*\sin \left(\mathrm{jy}\right)*\cos \left(\mathrm{jx}\right)+\sin \left(\mathrm{jz}\right)*\sin \left(\mathrm{jx}\right))*\mathrm{biz}+\mathrm{kx}\\ \sin \left(\mathrm{jz}\right)*\cos \left(\mathrm{jy}\right)*\mathrm{bix}+(\sin \left(\mathrm{jz}\right)*\sin \left(\mathrm{jy}\right)*\sin \left(\mathrm{jx}\right)+\cos \left(\mathrm{jz}\right)*\cos \left(\mathrm{jx}\right))*\mathrm{biy}+(\sin \left(\mathrm{jz}\right)*\sin \left(\mathrm{jy}\right)*\cos \left(\mathrm{jx}\right)-\cos \left(\mathrm{jz}\right)*\sin \left(\mathrm{jx}\right))*\mathrm{biz}+\mathrm{ky}\\ -\sin \left(\mathrm{jy}\right)*\mathrm{bix}+\cos \left(\mathrm{jy}\right)*\sin \left(\mathrm{jx}\right)*\mathrm{biy}+\cos \left(\mathrm{jy}\right)*\cos \left(\mathrm{jx}\right)*\mathrm{biz}+\mathrm{kz}\end{array}\right]---\left(2\right)$

Di is made to equal the difference of ai and bi '

$\mathrm{di}=\left[\begin{array}{c}\mathrm{dix}\\ \mathrm{diy}\\ \mathrm{diz}\end{array}\right]=\left[\begin{array}{c}\mathrm{aix}-{\mathrm{bi}}^{\′}x\\ \mathrm{aiy}-{\mathrm{bi}}^{\′}y\\ \mathrm{aiz}-{\mathrm{bi}}^{\′}z\end{array}\right]---\left(3\right)$

We wish bi(i=1 ... n) coordinate value after coordinate transform as far as possible close to ai, because more close to ai, should show that constructed coordinate transform formula is more accurate.With least square method constructed fuction F (jx, jy, jz, kx, ky, kz):

$F=\underset{i=1}{\overset{n}{\mathrm{\Σ}}}(\mathrm{dix}^2+\mathrm{diy}^2+\mathrm{diz}^2)---\left(4\right)$

Such problem just becomes jx, j y, jz, kx, ky, kz of asking and making function F (jx, jy, jz, kx, ky, kz) obtain minimum of a value.

First making for minimizing function F get first-order partial derivative respectively to variable jx, j y, jz, kx, ky, kz, setting up equation group (5):

$\left\{\begin{array}{c}\frac{\∂F}{\∂\mathrm{jx}}=0\\ \frac{\∂F}{\∂\mathrm{jy}}=0\\ \frac{\∂F}{\∂\mathrm{jz}}=0\\ \frac{\∂F}{\mathrm{kk}}=0\\ \frac{\∂F}{\∂\mathrm{ky}}=0\\ \frac{\∂F}{\∂\mathrm{kz}}=0\end{array}\right.---\left(5\right)$

Because equation group (5) is Nonlinear System of Equations, iterative algorithm can be used to solve, here for Newton method.

Order $f1(\mathrm{jx},\mathrm{jy},\mathrm{jz},\mathrm{kx},\mathrm{ky},\mathrm{kz})=\frac{\∂F}{\∂\mathrm{jx}}$

$f2(\mathrm{jx},\mathrm{jy},\mathrm{jz},\mathrm{kx},\mathrm{ky},\mathrm{kz})=\frac{\∂F}{\∂\mathrm{jy}}$

$f3(\mathrm{jx},\mathrm{jy},\mathrm{jz},\mathrm{kx},\mathrm{ky},\mathrm{kz})=\frac{\∂F}{\∂\mathrm{jz}}$

$f4(\mathrm{jx},\mathrm{jy},\mathrm{jz},\mathrm{kx},\mathrm{ky},\mathrm{kz})=\frac{\∂F}{\∂\mathrm{kx}}$

$f5(\mathrm{jx},\mathrm{jy},\mathrm{jz},\mathrm{kx},\mathrm{ky},\mathrm{kz})=\frac{\∂F}{\∂\mathrm{ky}}$

$f6(\mathrm{jx},\mathrm{jy},\mathrm{jz},\mathrm{kx},\mathrm{ky},\mathrm{kz})=\frac{\∂F}{\∂\mathrm{kz}}$

If simple setting one group of initial value: jx0, jy0, jz0, kx0, ky0, kz0 bring equation group (5) into and obtain

$\left\{\begin{array}{c}f1(\mathrm{jx}0,\mathrm{jy}0,\mathrm{jz}0,\mathrm{kx}0,\mathrm{ky}0,\mathrm{kz}0)=k10\\ f2(\mathrm{jx}0,\mathrm{jy}0,\mathrm{jz}0,\mathrm{kx}0,\mathrm{ky}0,\mathrm{kz}0)=k20\\ f3(\mathrm{jx}0,\mathrm{jy}0,\mathrm{jz}0,\mathrm{kx}0,\mathrm{ky}0,\mathrm{kz}0)=k30\\ f4(\mathrm{jx}0,\mathrm{jy}0,\mathrm{jz}0,\mathrm{kx}0,\mathrm{ky}0,\mathrm{kz}0)=k40\\ f5(\mathrm{jx}0,\mathrm{jy}0,\mathrm{jz}0,\mathrm{kx}0,\mathrm{ky}0,\mathrm{kz}0)=k50\\ f6(\mathrm{jx}0,\mathrm{jy}0,\mathrm{jz}0,\mathrm{kx}0,\mathrm{ky}0,\mathrm{kz}0)=k60\end{array}\right.---\left(6\right)$

Make ki=fi (jx, jy, jz, kx, ky, kz) (i=1 ... 6); Then have:

$\left\{\begin{array}{c}k1-k10=\frac{\∂f1}{\∂\mathrm{jx}}(\mathrm{jx}-\mathrm{jx}0)+\frac{\∂f1}{\∂\mathrm{jy}}(\mathrm{jy}-\mathrm{jy}0)+\frac{\∂f1}{\∂\mathrm{jz}}(\mathrm{jz}-\mathrm{jz}0)+\frac{\∂f1}{\∂\mathrm{kx}}(\mathrm{kx}-\mathrm{kx}0)+\frac{\∂f1}{\∂\mathrm{ky}}(\mathrm{ky}-\mathrm{ky}0)+\frac{\∂f1}{\∂\mathrm{kz}}(\mathrm{kz}-\mathrm{kz}0)\\ k2-k20=\frac{\∂f2}{\∂\mathrm{jx}}(\mathrm{jx}-\mathrm{jx}0)+\frac{\∂f2}{\∂\mathrm{jy}}(\mathrm{jy}-\mathrm{jy}0)+\frac{\∂f2}{\∂\mathrm{jz}}(\mathrm{jz}-\mathrm{jz}0)+\frac{\∂f2}{\∂\mathrm{kx}}(\mathrm{kx}-\mathrm{kx}0)+\frac{\∂f2}{\∂\mathrm{ky}}(\mathrm{ky}-\mathrm{ky}0)+\frac{\∂f2}{\∂\mathrm{kz}}(\mathrm{kz}-\mathrm{kz}0)\\ k3-k30=\frac{\∂f3}{\∂\mathrm{jx}}(\mathrm{jx}-\mathrm{jx}0)+\frac{\∂f3}{\∂\mathrm{jy}}(\mathrm{jy}-\mathrm{jy}0)+\frac{\∂f3}{\∂\mathrm{jz}}(\mathrm{jz}-\mathrm{jz}0)+\frac{\∂f3}{\∂\mathrm{kx}}(\mathrm{kx}-\mathrm{kx}0)+\frac{\∂f3}{\∂\mathrm{ky}}(\mathrm{ky}-\mathrm{ky}0)+\frac{\∂f3}{\∂\mathrm{kz}}(\mathrm{kz}-\mathrm{kz}0)\\ k4-k40=\frac{\∂f4}{\∂\mathrm{jx}}(\mathrm{jx}-\mathrm{jx}0)+\frac{\∂f4}{\∂\mathrm{jy}}(\mathrm{jy}-\mathrm{jy}0)+\frac{\∂f4}{\∂\mathrm{jz}}(\mathrm{jz}-\mathrm{jz}0)+\frac{\∂f4}{\∂\mathrm{kx}}(\mathrm{kx}-\mathrm{kx}0)+\frac{\∂f4}{\∂\mathrm{ky}}(\mathrm{ky}-\mathrm{ky}0)+\frac{\∂f4}{\∂\mathrm{kz}}(\mathrm{kz}-\mathrm{kz}0)\\ k5-k50=\frac{\∂f5}{\∂\mathrm{jx}}(\mathrm{jx}-\mathrm{jx}0)+\frac{\∂f5}{\∂\mathrm{jy}}(\mathrm{jy}-\mathrm{jy}0)+\frac{\∂f5}{\∂\mathrm{jz}}(\mathrm{jz}-\mathrm{jz}0)+\frac{\∂f5}{\∂\mathrm{kx}}(\mathrm{kx}-\mathrm{kx}0)+\frac{\∂f5}{\∂\mathrm{ky}}(\mathrm{ky}-\mathrm{ky}0)+\frac{\∂f5}{\∂\mathrm{kz}}(\mathrm{kz}-\mathrm{kz}0)\\ k6-k60=\frac{\∂f6}{\∂\mathrm{jx}}(\mathrm{jx}-\mathrm{jx}0)+\frac{\∂f6}{\∂\mathrm{jy}}(\mathrm{jy}-\mathrm{jy}0)+\frac{\∂f6}{\∂\mathrm{fz}}(\mathrm{jz}-\mathrm{jz}0)+\frac{\∂f6}{\∂\mathrm{kx}}(\mathrm{kx}-\mathrm{kx}0)+\frac{\∂f6}{\∂\mathrm{kx}}(\mathrm{kx}-\mathrm{kx}0)+\frac{\∂f6}{\∂\mathrm{kz}}(\mathrm{kz}-\mathrm{kz}0)\end{array}\right.---\left(7\right)$

Make Δ ki=ki-ki0(i=1 ... 6), Δ jx=jx-jx0, Δ jy=jy-jy0, Δ jz=jz-jz0, Δ kx=kx-kx0, Δ ky=ky-ky0, Δ kz=kz-kz0

Write as matrix form:

$\left[\begin{array}{c}\mathrm{\Δk}1\\ \mathrm{\Δk}2\\ \mathrm{\Δk}3\\ \mathrm{\Δk}4\\ \mathrm{\Δk}5\\ \mathrm{\Δk}6\end{array}\right]=\left[\begin{array}{cccccc}\frac{\∂f1}{\∂\mathrm{jx}}& \frac{\∂f1}{\∂\mathrm{jy}}& \frac{\∂f1}{\∂\mathrm{jz}}& \frac{\∂f1}{\∂\mathrm{kx}}& \frac{\∂f1}{\∂\mathrm{ky}}& \frac{\∂f1}{\∂\mathrm{kz}}\\ \frac{\∂f2}{\∂\mathrm{jx}}& \frac{\∂f2}{\∂\mathrm{jy}}& \frac{\∂f2}{\∂\mathrm{jz}}& \frac{\∂f2}{\∂\mathrm{kx}}& \frac{\∂f2}{\∂\mathrm{ky}}& \frac{\∂f2}{\∂\mathrm{kz}}\\ \frac{\∂f3}{\∂\mathrm{jx}}& \frac{\∂f3}{\∂\mathrm{jy}}& \frac{\∂f3}{\∂\mathrm{jz}}& \frac{\∂f3}{\∂\mathrm{kx}}& \frac{\∂f3}{\∂\mathrm{ky}}& \frac{\∂f3}{\∂\mathrm{kz}}\\ \frac{\∂f4}{\∂\mathrm{jx}}& \frac{\∂f4}{\∂\mathrm{jy}}& \frac{\∂f4}{\∂\mathrm{jz}}& \frac{\∂f4}{\∂\mathrm{kx}}& \frac{\∂f4}{\∂\mathrm{ky}}& \frac{\∂f4}{\∂\mathrm{kz}}\\ \frac{\∂f5}{\∂\mathrm{jx}}& \frac{\∂f5}{\∂\mathrm{jy}}& \frac{\∂f5}{\∂\mathrm{jz}}& \frac{\∂f5}{\∂\mathrm{kx}}& \frac{\∂f5}{\∂\mathrm{ky}}& \frac{\∂f5}{\∂\mathrm{kz}}\\ \frac{\∂f6}{\∂\mathrm{jx}}& \frac{\∂f6}{\∂\mathrm{jy}}& \frac{\∂f6}{\∂\mathrm{jz}}& \frac{\∂f6}{\∂\mathrm{kx}}& \frac{\∂f6}{\∂\mathrm{ky}}& \frac{\∂f6}{\∂\mathrm{kz}}\end{array}\right]*\left[\begin{array}{c}\mathrm{\Δjx}\\ \mathrm{\Δjy}\\ \mathrm{\Δjz}\\ \mathrm{\Δkx}\\ \mathrm{\Δky}\\ \mathrm{\Δkz}\end{array}\right]---\left(8\right)$

Equation group (8) is system of linear equations, and the full pivoting elimination approach of Gauss can be adopted to solve Δ jx, Δ jy, Δ jz, Δ kx, Δ ky, Δ kz.

With Δ jx, Δ jy, Δ jz, Δ kx, Δ ky, Δ kz, initial value is revised, makes initial value:

jx0＝jx0+Δjx；jy0＝jy0+Δjy；jz0＝jz0+Δjz；kx0=kx0+Δkx；ky0=ky0+Δky；kz0=kz0+Δkz；

New initial value is substituted into formula (8) continue to solve, until Δ ki is less than permissible accuracy, thus draws the value of six parameters of transformation matrix of coordinates, thus obtain measurement data coordinate a little in same coordinate system.

But, the precondition obtaining desired solution by equation group (5) is for it provides one group of suitable initial value, if the initial value provided is improper, obtains the solution come and can only make function F (jx, jy, jz, kx, ky, kz) in its a certain domain of definition, obtain minimum, but function F can not be made to obtain minimum of a value in global scope, like this, carry out by the solution of equation group (5) object that coordinate transform just not easily reaches our data fitting.

Therefore, need to provide the initial value that a group suitable in iterative process, just can obtain converging to the solution making function F obtain minimum of a value, thus carry out fast and accurately.

Below, emphasis describes in detail to the acquisition of iterative initial value in step S2:

Iterative initial value of the prior art, due to the arbitrariness of its value, therefore causes it can not obtain minimum of a value in global scope, and therefore, the present invention considers to go out to send the more suitable initial value of searching from common point.

Because three points not on the same line can determine the locus of a rectangular coordinate system, therefore, the present invention then first uses three common points corresponding arbitrarily in two groups of data (coordinate of each common point in former rectangular coordinate system and target-based coordinate system), and must be not three common points point-blank, carry out the parameters in rough calculation coordinate transform, then it can be used as initial value to substitute into Iterative Matrix iterative.

Choose not three points on the same line, be respectively the first common point, the second common point and the 3rd common point, these three points can be the parts constructing the common point that regression function is used in step S1, may not be in step S 1 common point constructing regression function and use.In conversion process, the coordinate of these three common points in target rectangular coordinate system is a1 (a1x, a1y, a1z), a2 (a2x, a2y, a2z), a3 (a3x, a3y, a3z); The coordinate of these three common points in former rectangular coordinate system is b1 (b1x, b1y, b1z), b2 (b2x, b2y, b2z), b3 (b3x, b3y, b3z).As shown in Figure 1, we divide nine steps to carry out six parameters of calculating coordinate change, also namely obtain the iterative initial value of iteration function:

Step S21: respectively by the origin translation of these two coordinate systems one of them common point place to respective coordinate system.

Such as move to first common point place, the changes in coordinates of these three common points is like this: a1 (0,0,0), a2 (a2x-a1x, a2y-a1y, a2z-a1z), a3 (a3x-a1x, a3y-a1y, a3z-a1z); B1 (0,0,0), b2 (b2x-b 1x, b2y-b1y, b2z-b1z), b3 (b3x-b1x, b3y-b1y, b3z-b1z).

Step S22: utilize three respective common points to set up a plane respectively in two coordinate systems.

Plane equation is respectively:

(a2y*a3z-a2z*a3y)*x+(a3x*a2z-a2x*a3z)*y+(a2x*a3y-a3x*a2y)*z=0(9)

(b2y*b3z-b2z*b3y)*x+(b3x*b2z-b2x*b3z)*y+(b2x*b3y-b3x*b2y)*z=0(10)

Step S23: around the X-axis anglec of rotation jix (i=1,2) of respective coordinate system, rotates to the Y-axis of respective coordinate system in 3 planes set up, recalculates the coordinate value of the second common point and the 3rd common point after rotating.

Wherein, anglec of rotation jix acquiring method is as follows:

Obtain the YZ plane of respective coordinate system and the intersection of 3 planes:

(a3x*a2z-a2x*a3z)*y+(a2x*a3y-a3x*a2y)*z=0；(11)

(b3x*b2z-b2x*b3z)*y+(b2x*b3y-b3x*b2y)*z=0；(12)

Obtain the angle jix (i=1,2) of respective Y-axis and this intersection.

Step S24: with the Y-axis anglec of rotation jiy (i=1,2) of the method identical with step S23 around respective coordinate system, rotates to X-axis in the plane of three common points foundation, recalculates the coordinate value of the second common point and the 3rd common point after rotating.

Step S25: X-axis is rotated on the second respective common point around the Z axis anglec of rotation jiz (i=1,2) of respective coordinate system.Recalculate the coordinate value of the second common point and the 3rd common point after rotating.

Angle jiz can be tried to achieve by the coordinate value of current second common point.

Step S26: judge that whether the current attitude of two coordinate systems is consistent according to respective second common point and the coordinate value of the 3rd common point, by coordinate system rotation, coordinate system 2 is become as inconsistent consistent with coordinate system 1, here attitude is inconsistent, mainly the direction of the Z axis of two coordinate systems may be contrary, if contrary, the Z axis of one of them coordinate system is revolved turnback, is described so that the Z axis of former coordinate system is revolved turnback below.

Above step S21-step S26 is in fact by translation of axes and rotation process, makes by the determined former rectangular coordinate system of described three common points consistent with the attitude of target right angle Two coordinate system; When carrying out translation and rotation process, as long as it is consistent finally can to reach attitude, does not limit the order between translation and rotation, not limiting the rotational order to each reference axis yet.

Step S27: calculate the rotational transformation matrix from former coordinate system transformation to target-based coordinate system.

If:

[RiX]: around the rotational transformation matrix (i=1,2) of the X-axis of coordinate system i;

[RiY]: around the rotational transformation matrix of the Y-axis of coordinate system i;

[RiZ]: around the rotational transformation matrix of the Z axis of coordinate system i;

[R2M]: the attitude rectification rotational transformation matrix of former coordinate system.

Then can calculate rotational transformation matrix [MZ]=[R1X] * [R1Y] * [R1Z] * [R2M] * [R2Z] * [R2Y] * [R2X] transforming to coordinate system 1 from coordinate system 2, wherein obtain in the step of the corner of each step above.

Step S28: calculate from former coordinate system transformation to target-based coordinate system rotational transformation matrix jx, jy, jz.

[MZ] can simplify and be expressed as following form:

$\mathrm{MZ}=\left[\begin{array}{ccc}{r}_{11}& r_{12}& r_{13}\\ r_{21}& r_{22}& r_{23}\\ r_{31}& r_{32}& r_{33}\end{array}\right]---\left(13\right)$

We know the transformation matrix around fixed coordinate system three X-axis rotate:

$\left[\mathrm{MG}\right]=\left[\begin{array}{ccc}\cos \mathrm{jz}\×\cos \mathrm{jy}& \cos \mathrm{jz}\×\sin \mathrm{jy}\×\sin \mathrm{jx}-\sin \mathrm{jz}\×\cos \mathrm{jx}& \cos \mathrm{jz}\×\sin \mathrm{jy}\×\cos \mathrm{jx}+\sin \mathrm{jz}\×\sin \mathrm{jx}\\ \sin \mathrm{jz}\×\cos \mathrm{jy}& \sin \mathrm{jz}\×\sin \mathrm{jy}\×\sin \mathrm{jx}+\cos \mathrm{jz}\×\cos \mathrm{jx}& \sin \mathrm{jz}\×\sin \mathrm{jy}\×\mathrm{clsjx}-\cos \mathrm{jz}\×\sin \mathrm{jx}\\ -\sin \mathrm{jy}& \cos \mathrm{jy}\×\sin \mathrm{jx}& \cos \mathrm{jy}\×\cos \mathrm{jx}\end{array}\right]---\left(14\right)$

Utilize formula (13), (14) are counter from rotational transformation matrix [MZ] solves jx, jy, jz.

This is one group of transcendental equation, has 3 unknown numbers, totally 9 equations, wherein has 6 equations not independent, wherein 3 equations therefore can be utilized to solve 3 unknown numbers.

Can find out:

$\cos \mathrm{jy}\sqrt{r_{11}^2+r_{21}^2}---\left(15\right)$

If cosjy ≠ 0, then obtain the arc tangent expression formula at each angle:

jx＝Atan2(r ₃₂,r ₃₃)；

$\mathrm{jy}=A\tan 2(-r_{31},\sqrt{r_{11}^2+r_{21}^2});$

jz＝Atan2(r ₂₁,r ₁₁)；

Step S29: calculate translational movement kx, ky, the kz from former coordinate system transformation to target-based coordinate system.

Former coordinate system does rotation transformation, makes former coordinate system parallel with original target-based coordinate system, asks the position relationship of the first common point in the first common point and target-based coordinate system in former coordinate system at this moment, then translational movement:

kx＝a1x-b1x；

ky＝a1y-b1y；

kz＝a1z-b1z；

We just obtain six whole initial values like this, also whole six parameters transforming to the transformation matrix of target rectangular coordinate system from former rectangular coordinate system are namely obtained, with these six parameters, as one group of initial value, be brought into equation group (5) as initial value, obtain the Iterative Matrix (8) based on above-mentioned initial value, carry out iteration, until Δ ki is less than permissible accuracy, actual coordinate conversion parameter can be obtained.

After obtaining actual coordinate conversion parameter, namely can carry out coordinate transform according to coordinate conversion parameter, and then the coordinate system completing impact point measurement data is unified.

Introduce the coordinate transform data treating apparatus of the embodiment of the present invention below again.

As shown in Figure 2, the coordinate transform data treating apparatus of the embodiment of the present invention, same for by the coordinate data conversion process in former rectangular coordinate system being the data in target rectangular coordinate system, and requiring that former rectangular coordinate system and described target rectangular coordinate system have the common point not on same straight line of more than at least three, described coordinate transform data treating apparatus comprises constructing module, Initial Value module, iteration module and conversion module.

Constructing module, in order to receive the coordinate data in former rectangular coordinate system and these two coordinate systems of target rectangular coordinate system of common point, construct regression function with the described coordinate data least square method of part or all of described common point, and draw and make regression function obtain the Iterative Matrix of minimum of a value solution by iteration; Initial Value module, for calculating the coordinate conversion parameter initial value between former rectangular coordinate system and target rectangular coordinate system with the common point of three not on same straight line; Iteration module: the initial value of the described Iterative Matrix that the described coordinate conversion parameter initial value calculated using described Initial Value module obtains as described constructing module carries out iteration, iteration is to obtaining actual coordinate conversion parameter when meeting required precision; Conversion module: the actual coordinate conversion parameter obtained by described iteration module obtain former rectangular coordinate system coordinate a little in target rectangular coordinate system.

Preferably, in described iteration module, comprise the authentication unit verifying described actual coordinate conversion parameter accuracy by the described coordinate data of the described common point of part.In addition, described Initial Value module can comprise pose adjustment submodule and calculating sub module, wherein, and pose adjustment submodule, for by translation of axes and rotation process, make by the determined former rectangular coordinate system of described three common points consistent with the attitude of target right angle Two coordinate system; And calculating sub module, for calculating the rotational transformation matrix from former coordinate system transformation to target-based coordinate system, and calculate described coordinate conversion parameter initial value further.

From the angle of refinement, Initial Value module can comprise nine unit, respectively: translation unit, for choosing three common points not on same straight line, respectively by the origin translation of described two coordinate systems one of them common point place to respective coordinate system; Plane sets up unit, sets up a plane in order to utilize described three common points respectively at described two coordinate systems; First computing unit, is rotating to the Y-axis of respective coordinate system around the X-axis of respective coordinate system described plane and is setting up the coordinate value of two other common point after in plane that unit sets up in order to recalculate; Second computing unit, in order to calculate two other common point described at the first computing unit coordinate value after recalculate with the method identical with described first computing unit around the Y-axis of respective coordinate system X-axis rotated to described plane set up after in plane that unit sets up described in the coordinate value of two other common point; 3rd computing unit, in order to calculate two other common point described at the second computing unit coordinate value after the Z axis recalculated around respective coordinate system X-axis is rotated to respective described in after one of two other common point described in the coordinate value of two other common point; Pose adjustment unit, in order to calculate two other common point described at the 3rd computing unit coordinate value after judge that whether the current attitude of described two coordinate systems consistent according to the coordinate value of two other common point described, as inconsistent, make the attitude of described two coordinate systems consistent by the Z axis of one of them coordinate system of rotation; 4th computing unit, in order to calculate the rotational transformation matrix transforming to target rectangular coordinate system from former rectangular coordinate system; 5th computing unit, in order to calculate from former rectangular coordinate system transform to target rectangular coordinate system rotational transformation matrix each rotation parameter; 6th computing unit, in order to calculate the translation parameters transforming to target rectangular coordinate system from former rectangular coordinate system.

The coordinate transform data treating apparatus of the embodiment of the present invention, also can comprise and select module and summarizing module, for the treatment of the measurement data that measuring instrument gathers from multiple erect-position, the described measurement data of each described erect-position is based on a rectangular coordinate system of respective erect-position, the rectangular co-ordinate of described one of them erect-position of selection model choice is target rectangular coordinate system, by the described measurement data of all the other erect-positions through described constructing module, described Initial Value module, described iteration module and described conversion module, the described summarizing module connected by described conversion module output draw each erect-position coordinate a little in described target rectangular coordinate system.

The coordinate transform data processing method of the embodiment of the present invention and device, a large amount of measured data and Lay Ka, FARO tracker Survey Software is utilized to compare, all demonstrate accuracy and the high efficiency of coordinate transform data processing method of the present invention, lift one group of representational data below and illustrate:

Have the point of one group of spatial distribution, wherein P1-P11 participates in the common point of matching, and M1-M8 is the common point carrying out data accuracy checking, and their coordinates in target rectangular coordinate system are as shown in table 1:

Table 1

Point identification	X	Y	Z
				P1	1816.1716	-2191.3525	3005.5751
P2	1813.7387	-2189.4396	2934.1564
				P3	1814.056	-2260.0048	2927.3241
P4	1377.6407	-2191.0715	2987.4365
				P5	978.0035	-2261.187	2910.2497
P6	1940.7238	-2191.02	2983.943
				P7	1660.9106	-2191.4248	3009.215
P8	1660.5513	-2188.8867	2923.074
				P9	1661.7163	-2259.5642	2916.1043
P10	1513.9315	-2259.6447	2912.1118
				P11	1243.1777	-2191.0945	2987.0547
M1	1478.3761	-2257.8882	3014.2295
				M2	1432.6217	-2257.9923	3017.7572
M3	1434.1124	-2258.5225	3035.8522
				M4	1479.6889	-2258.4188	3032.3254
M5	1412.2861	-2260.4429	3031.4108
				M6	1396.428	-2260.3072	3027.4152
M7	1400.0576	-2261.0156	3050.8963
				M8	1414.0208	-2260.7404	3042.2607

Their coordinates in former rectangular coordinate system are as shown in table 2:

Table 2

Point identification	X	Y	Z
				P1	324.28122	12988.851	-1799.2815
P2	392.00748	12978.787	-1778.737
				P3	403.38715	13047.491	-1765.4518
P4	221.57278	12923.802	-1377.5492
				P5	190.89428	12927.087	-965.68525
P6	379.12206	13003.982	-1912.1745
				P7	278.27544	12967.093	-1652.5528
P8	360.65256	12955.096	-1630.261
				P9	372.40376	13024.017	-1617.7275
P10	335.76861	13002.5	-1476.1252
				P11	185.11783	12904.533	-1249.5642
M1	227.93949	13006.884	-1469.1289
				M2	212.03197	13000.823	-1426.5127
M3	195.11505	13003.543	-1432.5418
				M4	210.97294	13009.579	-1474.989
M5	193.52799	13001.82	-1410.3087
				M6	193.00955	12998.978	-1394.2116
M7	171.52278	13002.77	-1403.6441
				M8	183.6133	13003.551	-1414.7269

The difference of two cover coordinates is as shown in table 3:

Table 3

Point identification	△X	△Y	△Z
				P1	1491.8904	-15180.203	4804.8566
P2	1421.7312	-15168.226	4712.8934
				P3	1410.6689	-15307.495	4692.7759
P4	1156.0679	-15114.874	4364.9858
				P5	787.10922	-15188.274	3875.9349

P6	1561.6017	-15195.002	4896.1175
				P7	1382.6352	-15158.518	4661.7678
P8	1299.8987	-15143.983	4553.335
				P9	1289.3125	-15283.581	4533.8317
P10	1178.1629	-15262.145	4388.237
				P11	1058.0599	-15095.627	4236.6189
M1	1250.4366	-15264.772	4483.3583
				M2	1220.5897	-15258.816	4444.27
M3	1238.9974	-15262.066	4468.394
				M4	1268.716	-15267.998	4507.3144
M5	1218.7581	-15262.263	4441.7195
				M6	1203.4185	-15259.285	4421.6269
M7	1228.5348	-15263.786	4454.5404
				M8	1230.4075	-15264.291	4456.9877

Changed in target rectangular coordinate system by point in former rectangular coordinate system, get common point P1 ~ P11 and do matching, the result of transformation result and common point M1-M8 is as shown in table 4:

Table 4

Point identification	X	Y	Z
				P1	1816.1716	-2191.3525	3005.5751
P2	1813.7387	-2189.4396	2934.1564
				P3	1814.056	-2260.0048	2927.3241
P4	1377.6407	-2191.0715	2987.4365
				P5	978.0035	-2261.187	2910.2497
P6	1940.7238	-2191.02	2983.943
				P7	1660.9106	-2191.4248	3009.215
P8	1660.5513	-2188.8867	2923.074
				P9	1661.7163	-2259.5642	2916.1043
P10	1513.9315	-2259.6447	2912.1118
				P11	1243.1777	-2191.0945	2987.0547

M1	1478.3761	-2257.8882	3014.2295
				M2	1432.6217	-2257.9923	3017.7572
M3	1434.1124	-2258.5225	3035.8522
				M4	1479.6889	-2258.4188	3032.3254
M5	1412.2861	-2260.4429	3031.4108
				M6	1396.428	-2260.3072	3027.4152
M7	1400.0576	-2261.0156	3050.8963
				M8	1414.0208	-2260.7404	3042.2607

Six parameters drawn through the coordinate transform data processing method of the embodiment of the present invention are:

The angle of rotating around the X, Y, Z axis of former coordinate system is (radian):

RX 2.7420 RY 1.2850 RZ -0.2404

The origin of coordinates along the distance of X, Y, Z axis movement is:

X -1843.3988 Y 10305.0729 Z 1424.5272

Utilize the difference of the coordinate after six above-mentioned Parameter Switch and the coordinate of common point in target-based coordinate system described in table 2 as shown in table 5:

Table 5

Call the roll	△X	△Y	△Z
				P1	0	0	0
P2	0	0	0
				P3	0	0	0
P4	0	0	0
				P5	0	0	0
P6	0	0	0
				P7	0	0	0
P8	0	0	0
				P9	0	0	0
P10	-0.000001	0	0
				P11	0	0	0
M1	0	0.000001	0

M2	0	0	0
				M3	0	0	0
M4	0	0	0
				M5	0	0.000001	0
M6	0	0	0
				M7	0	0.000001	0
M8	0	0	0

The data of table 5 show, coordinate transform data processing method of the present invention and device have higher accuracy, and the time of iteration convergence also shortens, and therefore improves the efficiency of coordinate transform data process.

The change that those skilled in the art do when should recognize the scope and spirit of the present invention disclosed in the claim do not departed from appended by the present invention and retouching, within the protection domain all belonging to claim of the present invention.

Claims (10)

1. a coordinate transform data processing method, coordinate system for impact point measurement data is unified, former rectangular coordinate system and target rectangular coordinate system have the common point not on same straight line of more than at least three, it is characterized in that, described coordinate transform data processing method comprises:

Step S1: the coordinate data in described former rectangular coordinate system and these two coordinate systems of described target rectangular coordinate system receiving described common point, obtain regression function with the described coordinate data of part or all of described common point, and draw and make described regression function obtain the Iterative Matrix of minimum of a value by iteration;

Step S2: obtain the coordinate conversion parameter initial value between described former rectangular coordinate system and described target rectangular coordinate system with three common points not on same straight line; Wherein: step S2 comprises:

Step S21: choose three common points not on same straight line, respectively by the same common point place of the origin translation of described two coordinate systems to respective coordinate system;

Step S22: utilize described three common points to set up a plane respectively at described two coordinate systems;

Step S3: the described coordinate conversion parameter initial value calculated using described step S1 carries out iteration as the initial value of described Iterative Matrix, iteration is to obtaining actual coordinate conversion parameter when meeting required precision;

Step S4: the actual coordinate conversion parameter obtained with step S3 obtain described former rectangular coordinate system coordinate a little in described target rectangular coordinate system.

2. coordinate transform data processing method as claimed in claim 1, is characterized in that, in step s3, comprises the step verifying described actual coordinate conversion parameter accuracy by the described coordinate data of the described common point of part.

3. coordinate transform data processing method as claimed in claim 2, it is characterized in that, the step of the coordinate conversion parameter initial value that three common points of described use not on same straight line calculate between former rectangular coordinate system and target rectangular coordinate system also comprises:

By translation of axes and rotation process, make by the determined described former rectangular coordinate system of described three common points step consistent with the attitude of described target rectangular coordinate system; And

Obtain the rotational transformation matrix transforming to described target rectangular coordinate system from described former rectangular coordinate system, and obtain the step of described coordinate conversion parameter initial value further.

4. coordinate transform data processing method as claimed in claim 2, it is characterized in that, described step S2 also comprises:

Step S23: the X-axis around respective coordinate system rotates to the Y-axis of respective coordinate system in described plane, recalculates the coordinate value of two other common point postrotational;

Step S24: X-axis rotated in described plane by the Y-axis of the method identical with step S23 around respective coordinate system, regains the coordinate value of postrotational two other common point described;

Step S25: around respective coordinate system Z axis X-axis rotate to respective described in one of two other common point, regain the coordinate value of postrotational two other common point described;

Step S26: the coordinate value according to two other common point described judges that whether the current attitude of described two coordinate systems is consistent, as inconsistent, makes the attitude of described two coordinate systems consistent by the Z axis of one of them coordinate system of rotation;

Step S27: obtain the described rotational transformation matrix transforming to described target rectangular coordinate system from former rectangular coordinate system;

Step S28: obtain from described former rectangular coordinate system transform to described target rectangular coordinate system rotational transformation matrix each rotation parameter;

Step S29: obtain the translation parameters transforming to described target rectangular coordinate system from described former rectangular coordinate system.

5. coordinate transform data processing method as claimed in claim 1, it is characterized in that, described coordinate data is the measurement data that measuring instrument gathers from multiple erect-position, the described measurement data of each described erect-position is based on a rectangular coordinate system of respective erect-position, the rectangular co-ordinate of one of them erect-position is selected to be target rectangular coordinate system, by the described measurement data of all the other erect-positions successively through described step S1, step S2, step S3 and step S4, draw each erect-position coordinate a little in described target rectangular coordinate system.

6. a coordinate transform data treating apparatus, coordinate system for measurement data is unified, former rectangular coordinate system and target rectangular coordinate system have the common point not on same straight line of more than at least three, it is characterized in that, described coordinate transform data treating apparatus comprises:

Constructing module, in order to receive the coordinate data in former rectangular coordinate system and these two coordinate systems of target rectangular coordinate system of common point, construct regression function with the described coordinate data least square method of part or all of described common point, and draw and make regression function obtain the Iterative Matrix of minimum of a value solution by iteration;

Initial Value module: for obtaining the coordinate conversion parameter initial value between former rectangular coordinate system and target rectangular coordinate system with the common point of three not on same straight line; Described Initial Value module comprises:

Translation unit, for choosing three common points not on same straight line, respectively by the same common point place of the origin translation of described two coordinate systems to respective coordinate system;

Plane sets up unit, sets up a plane in order to utilize described three common points respectively at described two coordinate systems;

Iteration module: the initial value of the described Iterative Matrix that the described coordinate conversion parameter initial value obtained using described Initial Value module obtains as described constructing module carries out iteration, iteration is to obtaining actual coordinate conversion parameter when meeting required precision;

Conversion module: the actual coordinate conversion parameter obtained by described iteration module obtain former rectangular coordinate system coordinate a little in target rectangular coordinate system.

7. coordinate transform data treating apparatus as claimed in claim 6, is characterized in that, in described iteration module, comprises the authentication unit verifying described actual coordinate conversion parameter accuracy by the described coordinate data of the described common point of part.

8. coordinate transform data treating apparatus as claimed in claim 7, it is characterized in that, described Initial Value module also comprises:

Pose adjustment submodule, for by translation of axes and rotation process, makes by the determined former rectangular coordinate system of described three common points consistent with the attitude of target rectangular coordinate system Two coordinate system; And

Calculating sub module, for obtaining the rotational transformation matrix from former coordinate system transformation to target-based coordinate system, and calculates described coordinate conversion parameter initial value further.

9. coordinate transform data treating apparatus as claimed in claim 7, it is characterized in that, described Initial Value module also comprises:

First computing unit, is rotating to the Y-axis of respective coordinate system around the X-axis of respective coordinate system described plane and is setting up the coordinate value of two other common point after in plane that unit sets up in order to recalculate;

Second computing unit, in order to calculate two other common point described at the first computing unit coordinate value after recalculate with the method identical with described first computing unit around the Y-axis of respective coordinate system X-axis rotated to described plane set up after in plane that unit sets up described in the coordinate value of two other common point;

3rd computing unit, in order to calculate two other common point described at the second computing unit coordinate value after the Z axis recalculated around respective coordinate system X-axis is rotated to respective described in after one of two other common point described in the coordinate value of two other common point;

Pose adjustment unit, in order to calculate two other common point described at the 3rd computing unit coordinate value after judge that whether the current attitude of described two coordinate systems consistent according to the coordinate value of two other common point described, as inconsistent, make the attitude of described two coordinate systems consistent by the Z axis of one of them coordinate system of rotation;

4th computing unit, in order to calculate the rotational transformation matrix transforming to target rectangular coordinate system from former rectangular coordinate system;

5th computing unit, transforms to each rotation parameter the rotational transformation matrix of target rectangular coordinate system in order to calculate from former rectangular coordinate system;

6th computing unit, in order to calculate the translation parameters transforming to target rectangular coordinate system from former rectangular coordinate system.

10. coordinate transform data treating apparatus as claimed in claim 6, it is characterized in that, described coordinate transform data treating apparatus also comprises selects module and summarizing module, described coordinate data is the measurement data that measuring instrument gathers from multiple erect-position, the described measurement data of each described erect-position is based on a rectangular coordinate system of respective erect-position, the rectangular co-ordinate of described one of them erect-position of selection model choice is target rectangular coordinate system, by the described measurement data of all the other erect-positions through described constructing module, described Initial Value module, described iteration module and described conversion module, the described summarizing module connected by described conversion module output draw each erect-position coordinate a little in described target rectangular coordinate system.